Work

Visualizing Group Dynamics based on Multiparty Meeting Understanding

Year: 2018

Type: conference-paper

Abstract: Group discussions are usually aimed at sharing opinions, reaching consensus and making good decisions based on group knowledge.During a discussion, participants might adjust their own opinions as well as tune their attitudes towards others' opinions, based on the unfolding interactions.In this paper, we demonstrate a framework to visualize such dynamics; at each instant of a conversation, the participants' opinions and potential influence on their counterparts is easily visualized.We use multi-party meeting opinion mining based on bipartite graphs to extract opinions and calculate mutual influential factors, using the Lunar Survival Task as a study case.

Source: Conference on Empirical Methods in Natural Language Processing: System Demonstrations (EMNLP)

DOI: 10.18653/v1/d18-2017

Authors: Ni Zhang, Tongtao Zhang, Indrani Bhattacharya, Heng Ji, Rich Radke

Institution: Rensselaer Polytechnic Institute

Language: English

Topic: Opinion Dynamics and Social Influence

Subfield: Statistical and Nonlinear Physics

Field: Physics and Astronomy

Domain: Physical Sciences

Open Access status: hybrid

Funder: National Science Foundation

Award: PFI:BIC: Multimodal-Sensor-Enabled Environments with Advanced Cognitive Computing Enabling Smart Group Meeting Facilitation Services.